计算机体系结构,并行与分布式计算

Future Generation Computer Systems

Special Issue on "Data Exploration in the Web 3.0 Age"

摘要截稿:

全文截稿: 2019-01-20

影响因子: 4.639

期刊难度:

CCF分类: C类

中科院JCR分区:

• 大类 : 工程技术 - 2区

• 小类 : 计算机：理论方法 - 2区

Overview

Currently emerging Web 3.0 environments have provided a strong potential for the integration of data sources, applications and tools. In such a pervasive and highly dynamic scenario, existing techniques for accessing and managing web content seem to be actually inadequate to satisfy the user needs and more automatic ways of exploring, joining and sharing information are needed to improve the usability of web resources.

This raises several important challenges for future data and web mining methods. Such challenges range from the analysis of poorly structured information, such as annotations and tags, to the provision of intelligent methods that support users in searching and integrating information offered by web resources. The overall goal of these challenges is not limited to enhance information retrieval but also includes exploiting the enriched semantics a dataset acquires when used in conjunction with other sources of information. The synergy of different technologies, including semantic web, natural language search, machine learning, recommendation agents and artificial intelligence, can be especially fruitful in this perspective.

Furthermore, in the era of big data and Internet of things, we are increasingly dealing with a huge amount of information generated by heterogeneous sources. Indeed, almost every individual leaves digital traces when interacting with sensor networks, cloud services and positioning services, through a variety of mobile devices and smart objects. A growing attention is thus devoted to the design of suitable approaches for exploring this kind of data, in order to extract actionable knowledge about people, things, and their interactions.

More generally, the dimensionality and the complexity of gathered data is fast increasing in almost all applications domains, giving rise to the need of innovative data analysis approaches.

The goal of this FGCS special issue is to foster the dissemination of top-notch results in all the areas related to Data Exploration in a very broad sense, including contributions from data mining, query languages, semantic analysis, data visualization, graph databases and other fields related to the analysis and exploitation of data.

Topics of Interest

The topics of the call regard original contributions focusing on challenging aspects of data exploration in modern scenarios, in a broad sense. These may for instance be related to the followings: